Aims and Scope

Nowadays, Semantic Web applications have been used in a broad spectrum of domains such as ecommerce, geography, biology, or the public sector. With the development of semantic technologies, a huge amount of data is being published on the Semantic Web. The published data are evolving into the ”Web of Data” that is available on web-scale for retrieval and reuse of information. Considering the significant growth of data on the Semantic Web, one of the key challenges is the management of data quality in the Semantic Web. Moreover, the Semantic Web has brought up new technologies that may be useful to improve data quality management in information systems.

Over the last decade, data quality has become a critical factor to the success of organizations. Numerous business initiatives have been delayed or even cancelled due to poor data quality. Analogous to data in information systems, Semantic Web data also suffers from quality problems such as missing or false RDF data. In order to raise the level of trust in the Semantic Web data, it is valuable to investigate data quality issues in the context of the Semantic Web. Semantic technologies may provide new solution options for data quality management. Therefore we believe that in addition to applying previous data quality research on Semantic Web, there are opportunities of finding new data quality models, frameworks, methodologies, and applications by using semantic technologies.

The aim of this workshop is to bring the Semantic Web and data quality research communities together and identify new innovative possibilities for addressing data quality issues with semantic technologies. Moreover, we aim to provide a platform for discussing approaches, models, results, case studies, best practices, evaluation techniques, and implementation tools that are related to data quality management within Semantic Web.